Railroads have long been serving the largest portion of freight ton-miles in the U.S. freight shipment market. The rising demand for rail transportation is expected to continue in the foreseeable future, and considerable network congestion and inefficiency will result. Thus, a systematic methodology is needed to predict freight flow concentrations and congestion patterns in the rail network. A customized network assignment model for rail freight shipment demand is proposed: in this model, single- and double-track lines are represented by an equivalent directed graph. A railroad-specific link cost function adjusted for single and double tracks is developed to capture traffic delay, and an adapted convex combination algorithm is developed to find the shipment routing equilibrium. This model is applied to an empirical case study for the U.S. rail network with national freight shipment demand in 2007. The resulting freight flow pattern is visualized graphically and validated with empirical data. The proposed modeling framework could be used to help public agencies and private companies predict rail network traffic and develop infrastructure investment strategies to reduce adverse social impacts imposed by rail traffic delay.